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Learning Machine Translation - MIT Press Scholarship Online
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Learning Machine Translation

Cyril Goutte, Nicola Cancedda, Marc Dymetman, and George Foster


The Internet gives us access to a wealth of information in languages we don’t understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This book investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. It looks first at enabling technologies—technologies that solve problems which are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the ac ... More

Keywords: Internet, translation, machine learning techniques, statistical machine translation, enabling technologies, multilingual name dictionaries, word alignment, discriminative training framework, syntactic information, learning methods

Bibliographic Information

Print publication date: 2008 Print ISBN-13: 9780262072977
Published to MIT Press Scholarship Online: August 2013 DOI:10.7551/mitpress/9780262072977.001.0001


Affiliations are at time of print publication.

Cyril Goutte, editor

Nicola Cancedda, editor

Marc Dymetman, editor

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1 A Statistical Machine Translation Primer

Nicola Cancedda, Marc Dymetman, George Foster, and Cyril Goutte

I Enabling Technologies

2 Mining Patents for Parallel Corpora

Masao Utiyama, and Hitoshi Isahara

3 Automatic Construction of Multilingual Name Dictionaries

Bruno Pouliquen, and Ralf Steinberger

II Enabling Technologies

7 Toward Purely Discriminative Training for Tree-Structured Translation Models

Benjamin Wellington, Joseph Turian, and I. Dan Melamed

9 Kernel-Based Machine Translation

Zhuoran Wang, and John Shawe-Taylor

11 Discriminative Phrase Selection for SMT

Jesús Giménez, and Lluís Màrquez

12 Semisupervised Learning for Machine Translation

Nicola Ueffing, Gholamreza Haffari, and Anoop Sarkar

13 Learning to Combine Machine Translation Systems

Evgeny Matusov, Gregor Leusch, and Hermann Ney